http://iet.metastore.ingenta.com
1887

Enhancement of safety and comfort of cyclists at intersections

Enhancement of safety and comfort of cyclists at intersections

For access to this article, please select a purchase option:

Buy article PDF
£12.50
(plus tax if applicable)
Buy Knowledge Pack
10 articles for £75.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Name:*
Email:*
Your details
Name:*
Email:*
Department:*
Why are you recommending this title?
Select reason:
 
 
 
 
 
IET Intelligent Transport Systems — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

Cyclist safety is increasingly becoming a societal problem in Europe, as shown by road safety statistics. Frequent stops for red traffic lights at intersections are experienced by cyclists as a major inconvenience. This study introduces a green wave concept for cyclists, with focus on the traffic management and control aspects under cooperative intelligent transport systems applications. It especially addresses increasing stability of the adaptive control system, to overcome the drawbacks of both actuated and traditional adaptive control (which are too unpredictable for a green wave speed advice). In addition, solutions for avoiding increased delays for other traffic are investigated, as generally result from a classic green wave approach (with only fixed-time control) and traditional adaptive control. This study introduces an adaptive control algorithm for a real-time model-predictive controller and implements a plan-deviation cost function to address stabilisation. Simulation results show that the developed method increases stability of the adaptive control system, limits extra delays for other traffic and yields a high success rate for the green wave concept.

References

    1. 1)
      • 1. EROS.: ‘Traffic safety basic facts 2016 – cyclists’. EROS (European Road Safety Observatory), 2016.
    2. 2)
      • 2. Fietsersbond.: ‘Discussions on C-ITS service of traffic light prioritisation for designated VRUs’, The C-MobILE workshop, Helmond, 27 June 2017.
    3. 3)
      • 3. European Commission.: ‘Platform for the deployment of cooperative intelligent transport systems in the EU (E03188) (C-ITS platform) final report’. DG MOVE – DG Mobility and Transport, Brussels, January 2016.
    4. 4)
      • 4. C-MobILE Consortium.: ‘C-MobILE (accelerating C-ITS Mobility Innovation and depLoyment in Europe) description of work’. C-MobILE Consortium, Brussels, 2017 (restricted). Available at http://c-mobile-project.eu/: accessed January 2018.
    5. 5)
      • 5. Jiang, H., Hu, J., An, S., et al: ‘Eco approaching at an isolated signalized intersection under partially connected and automated vehicles environment’, Transp. Res. C, Emerg. Technol., 2017, 79, pp. 290307.
    6. 6)
      • 6. Hu, J., Shao, Y., Sun, M., et al: ‘Integrated optimal eco-driving on rolling terrain for hybrid electric vehicle with vehicle-infrastructure communication’, Transp. Res. C, Emerg. Technol., 2016, 68, pp. 228244.
    7. 7)
      • 7. Wang, M., Daamen, W., Hoogendoorn, S.P., et al: ‘Potential impacts of an optimization-based eco-acc system on traffic and environment’, IET Intell. Transp. Syst., 2014, 8, pp. 7786.
    8. 8)
      • 8. Blokpoel, R.J., Niebel, W.: ‘Advantage of cooperative traffic light control algorithms’. Proc. European Congress on Intelligent Transport Systems, Glasgow, UK, June 2016.
    9. 9)
      • 9. Stebbins, S., Hickman, M., Kim, J., et al: ‘Characterising green light optimal speed advisory trajectories for platoon-based optimisation’. Proc. Transportation Research Board (TRB) Annual Meeting, Washington, DC, USA, 2017.
    10. 10)
      • 10. Stebbins, S., Kim, J., Hickman, M., et al: ‘Combining model predictive intersection control with green light optimal speed advisory in a connected vehicle environment’. Proc. Transportation Research Board (TRB) Annual Meeting, Washington, DC, USA, 2017.
    11. 11)
      • 11. Blokpoel, R.J., Joueiai, M.: ‘Bicycle modelling in SUMO for accurate traffic simulation’. Proc. SUMO Conf., Berlin, Germany, 2016, pp. 110.
    12. 12)
      • 12. Blokpoel, R.J., Lu, M: ‘Signal plan stabilization to enable eco-driving’. Proc. IEEE Intelligent Transportation Systems Conf., Yokohama, October 2017.
    13. 13)
      • 13. XCycle Consortium.: ‘XCycle (advanced measures to reduce cyclists’ fatalities and increase comfort in the interaction with motorised vehicles) description of work’. XCycle Consortium, Brussels, 2015 (restricted). Available at www.xcycle-h2020.eu/: accessed January 2018.
    14. 14)
      • 14. Van Vliet, K., Turksma, S.: ‘ImFlow: policy-based adaptive urban traffic control first field experience’. Proc. European Congress on Intelligent Transport Systems, Dublin, Ireland, 2013.
    15. 15)
      • 15. M.A.V.E.N. Consortium: ‘MAVEN (managing automated vehicles enhances network) description of work’. MAVEN Consortium, Brussels, 2016 (restricted). Available at www.maven-its.eu: accessed January 2018.
    16. 16)
      • 16. Lu, M., Blokpoel, R.J.: ‘A sophisticated intelligent urban road-transport network and cooperative systems infrastructure for highly automated vehicles’. Proc. World Congress on Intelligent Transport Systems, October, Montreal, 2016.
http://iet.metastore.ingenta.com/content/journals/10.1049/iet-its.2017.0250
Loading

Related content

content/journals/10.1049/iet-its.2017.0250
pub_keyword,iet_inspecKeyword,pub_concept
6
6
Loading
This is a required field
Please enter a valid email address